Overview

Dataset statistics

Number of variables67
Number of observations5000
Missing cells147
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory523.1 B

Variable types

CAT26
BOOL22
NUM19

Warnings

CarValue has a high cardinality: 801 distinct values High cardinality
CardSpendMonth has a high cardinality: 4760 distinct values High cardinality
VoiceLastMonth has a high cardinality: 866 distinct values High cardinality
VoiceOverTenure has a high cardinality: 4438 distinct values High cardinality
EquipmentLastMonth has a high cardinality: 735 distinct values High cardinality
EquipmentOverTenure has a high cardinality: 1683 distinct values High cardinality
DataLastMonth has a high cardinality: 746 distinct values High cardinality
DataOverTenure has a high cardinality: 1328 distinct values High cardinality
PhoneCoTenure is highly correlated with CardTenureHigh correlation
CardTenure is highly correlated with PhoneCoTenureHigh correlation
LoanDefault_num is highly correlated with LoanDefaultHigh correlation
LoanDefault is highly correlated with LoanDefault_numHigh correlation
HomeOwner2 is highly correlated with HomeOwnerHigh correlation
HomeOwner is highly correlated with HomeOwner2High correlation
Gender_num is highly correlated with GenderHigh correlation
Gender is highly correlated with Gender_numHigh correlation
LoanDefault_num is highly correlated with LoanDefaultHigh correlation
LoanDefault is highly correlated with LoanDefault_numHigh correlation
CardSpendMonth is uniformly distributed Uniform
VoiceOverTenure is uniformly distributed Uniform
CustomerID has unique values Unique
EmploymentLength has 659 (13.2%) zeros Zeros
NumberPets has 1529 (30.6%) zeros Zeros
NumberCats has 3408 (68.2%) zeros Zeros
NumberDogs has 3755 (75.1%) zeros Zeros
NumberBirds has 4664 (93.3%) zeros Zeros
CarsOwned has 497 (9.9%) zeros Zeros
CardTenure has 91 (1.8%) zeros Zeros
TVWatchingHours has 85 (1.7%) zeros Zeros

Reproduction

Analysis started2021-12-17 12:01:32.743344
Analysis finished2021-12-17 12:02:53.775884
Duration1 minute and 21.03 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

CustomerID
Categorical

UNIQUE

Distinct5000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
9999-EGLHVE-19G
 
1
9108-FHQQBK-LAH
 
1
5252-VCMHWS-YAY
 
1
4603-GZODHR-TEP
 
1
9271-QHXIJE-VVI
 
1
Other values (4995)
4995 
ValueCountFrequency (%) 
9999-EGLHVE-19G1< 0.1%
 
9108-FHQQBK-LAH1< 0.1%
 
5252-VCMHWS-YAY1< 0.1%
 
4603-GZODHR-TEP1< 0.1%
 
9271-QHXIJE-VVI1< 0.1%
 
4306-FUNUCR-5M61< 0.1%
 
1967-XURQTC-5171< 0.1%
 
4119-CVVRLR-GX51< 0.1%
 
6354-FYYPEI-BS21< 0.1%
 
2665-KYMUNB-XHA1< 0.1%
 
Other values (4990)499099.8%
 
2021-12-17T07:02:53.954398image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5000 ?
Unique (%)100.0%
2021-12-17T07:02:54.137085image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length15
Mean length15
Min length15

Region
Real number (ℝ≥0)

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0014
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:02:54.287681image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.421760289
Coefficient of variation (CV)0.4736990369
Kurtosis-1.308981878
Mean3.0014
Median Absolute Deviation (MAD)1
Skewness0.005052460523
Sum15007
Variance2.02140232
MonotocityNot monotonic
2021-12-17T07:02:54.426276image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
5102720.5%
 
1100920.2%
 
3100320.1%
 
299519.9%
 
496619.3%
 
ValueCountFrequency (%) 
1100920.2%
 
299519.9%
 
3100320.1%
 
496619.3%
 
5102720.5%
 
ValueCountFrequency (%) 
5102720.5%
 
496619.3%
 
3100320.1%
 
299519.9%
 
1100920.2%
 

TownSize
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
1
1436 
2
1048 
3
907 
4
857 
5
750 
ValueCountFrequency (%) 
1143628.7%
 
2104821.0%
 
390718.1%
 
485717.1%
 
575015.0%
 
#NULL!2< 0.1%
 
2021-12-17T07:02:54.611021image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:02:54.748880image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:54.897192image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length1
Mean length1.002
Min length1

Gender
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing33
Missing (%)0.7%
Memory size39.1 KiB
Female
2494 
Male
2473 
ValueCountFrequency (%) 
Female249449.9%
 
Male247349.5%
 
(Missing)330.7%
 
2021-12-17T07:02:55.053770image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:02:55.158453image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:55.267163image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.991
Min length3

Age
Real number (ℝ≥0)

Distinct62
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.0256
Minimum18
Maximum79
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:02:55.458045image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile20
Q131
median47
Q362
95-th percentile76
Maximum79
Range61
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.77033769
Coefficient of variation (CV)0.3778864638
Kurtosis-1.187029996
Mean47.0256
Median Absolute Deviation (MAD)15
Skewness0.09076008705
Sum235128
Variance315.7849016
MonotocityNot monotonic
2021-12-17T07:02:55.667860image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
181062.1%
 
351022.0%
 
37982.0%
 
24971.9%
 
63951.9%
 
21951.9%
 
31941.9%
 
57931.9%
 
25931.9%
 
36921.8%
 
Other values (52)403580.7%
 
ValueCountFrequency (%) 
181062.1%
 
19781.6%
 
20801.6%
 
21951.9%
 
22821.6%
 
ValueCountFrequency (%) 
79731.5%
 
78701.4%
 
77711.4%
 
76581.2%
 
75741.5%
 

EducationYears
Real number (ℝ≥0)

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.543
Minimum6
Maximum23
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:02:55.898210image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9
Q112
median14
Q317
95-th percentile20
Maximum23
Range17
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.281082763
Coefficient of variation (CV)0.2256125121
Kurtosis-0.6070629191
Mean14.543
Median Absolute Deviation (MAD)2
Skewness0.003733520921
Sum72715
Variance10.7655041
MonotocityNot monotonic
2021-12-17T07:02:56.058784image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%) 
1456911.4%
 
1553610.7%
 
1353110.6%
 
164869.7%
 
124679.3%
 
174549.1%
 
113627.2%
 
183497.0%
 
193086.2%
 
102605.2%
 
Other values (8)67813.6%
 
ValueCountFrequency (%) 
680.2%
 
7310.6%
 
81072.1%
 
91783.6%
 
102605.2%
 
ValueCountFrequency (%) 
2340.1%
 
22330.7%
 
211112.2%
 
202064.1%
 
193086.2%
 

JobCategory
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Sales
1650 
Professional
1380 
Labor
686 
Service
620 
Crafts
452 
ValueCountFrequency (%) 
Sales165033.0%
 
Professional138027.6%
 
Labor68613.7%
 
Service62012.4%
 
Crafts4529.0%
 
Agriculture2124.2%
 
2021-12-17T07:02:56.253297image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:02:56.385909image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:56.546849image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length6
Mean length7.5248
Min length5
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
4244 
Yes
756 
ValueCountFrequency (%) 
No424484.9%
 
Yes75615.1%
 
2021-12-17T07:02:56.664568image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

EmploymentLength
Real number (ℝ≥0)

ZEROS

Distinct52
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7304
Minimum0
Maximum52
Zeros659
Zeros (%)13.2%
Memory size39.1 KiB
2021-12-17T07:02:56.798215image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q315
95-th percentile31
Maximum52
Range52
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.690928679
Coefficient of variation (CV)0.9959435048
Kurtosis1.052865428
Mean9.7304
Median Absolute Deviation (MAD)6
Skewness1.251917702
Sum48652
Variance93.91409866
MonotocityNot monotonic
2021-12-17T07:02:57.027707image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
065913.2%
 
13897.8%
 
23186.4%
 
33096.2%
 
42935.9%
 
52605.2%
 
62505.0%
 
71913.8%
 
81873.7%
 
111843.7%
 
Other values (42)196039.2%
 
ValueCountFrequency (%) 
065913.2%
 
13897.8%
 
23186.4%
 
33096.2%
 
42935.9%
 
ValueCountFrequency (%) 
521< 0.1%
 
511< 0.1%
 
491< 0.1%
 
481< 0.1%
 
471< 0.1%
 

Retired
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
4262 
Yes
738 
ValueCountFrequency (%) 
No426285.2%
 
Yes73814.8%
 
2021-12-17T07:02:57.151381image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

HHIncome
Real number (ℝ≥0)

Distinct266
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54759.6
Minimum9000
Maximum1073000
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:02:57.270483image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum9000
5-th percentile13000
Q124000
median38000
Q367000
95-th percentile147000
Maximum1073000
Range1064000
Interquartile range (IQR)43000

Descriptive statistics

Standard deviation55377.51115
Coefficient of variation (CV)1.01128407
Kurtosis57.07703653
Mean54759.6
Median Absolute Deviation (MAD)18000
Skewness5.179216362
Sum273798000
Variance3066668742
MonotocityNot monotonic
2021-12-17T07:02:57.463105image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
220001122.2%
 
290001092.2%
 
250001082.2%
 
300001022.0%
 
200001022.0%
 
180001002.0%
 
230001002.0%
 
24000992.0%
 
32000931.9%
 
21000911.8%
 
Other values (256)398479.7%
 
ValueCountFrequency (%) 
9000831.7%
 
10000551.1%
 
11000571.1%
 
12000521.0%
 
13000561.1%
 
ValueCountFrequency (%) 
10730001< 0.1%
 
9950001< 0.1%
 
7800001< 0.1%
 
6420001< 0.1%
 
5750001< 0.1%
 

DebtToIncomeRatio
Real number (ℝ≥0)

Distinct325
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.95416
Minimum0
Maximum43.1
Zeros1
Zeros (%)< 0.1%
Memory size39.1 KiB
2021-12-17T07:02:57.645319image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.9
Q15.1
median8.8
Q313.6
95-th percentile22.2
Maximum43.1
Range43.1
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation6.399783288
Coefficient of variation (CV)0.6429254993
Kurtosis1.37645844
Mean9.95416
Median Absolute Deviation (MAD)4
Skewness1.061933558
Sum49770.8
Variance40.95722614
MonotocityNot monotonic
2021-12-17T07:02:57.812761image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7481.0%
 
4.1460.9%
 
6.9460.9%
 
5.4450.9%
 
4.4420.8%
 
6.6420.8%
 
7.3410.8%
 
5.9390.8%
 
11.3390.8%
 
9.6380.8%
 
Other values (315)457491.5%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.160.1%
 
0.22< 0.1%
 
0.350.1%
 
0.460.1%
 
ValueCountFrequency (%) 
43.11< 0.1%
 
41.71< 0.1%
 
411< 0.1%
 
40.71< 0.1%
 
38.21< 0.1%
 

CreditDebt
Real number (ℝ≥0)

Distinct4902
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.857325646
Minimum0
Maximum109.072596
Zeros1
Zeros (%)< 0.1%
Memory size39.1 KiB
2021-12-17T07:02:58.000488image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.101088
Q10.3855195
median0.926437
Q32.06382
95-th percentile6.3730104
Maximum109.072596
Range109.072596
Interquartile range (IQR)1.6783005

Descriptive statistics

Standard deviation3.41573197
Coefficient of variation (CV)1.839059283
Kurtosis248.5334273
Mean1.857325646
Median Absolute Deviation (MAD)0.6517005
Skewness11.12004134
Sum9286.628229
Variance11.66722489
MonotocityNot monotonic
2021-12-17T07:02:58.196998image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.604840.1%
 
1.0903230.1%
 
0.7600322< 0.1%
 
0.879122< 0.1%
 
1.3442< 0.1%
 
0.081512< 0.1%
 
0.2192322< 0.1%
 
1.358282< 0.1%
 
0.210212< 0.1%
 
0.92752< 0.1%
 
Other values (4892)497799.5%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0013641< 0.1%
 
0.003411< 0.1%
 
0.004941< 0.1%
 
0.0063441< 0.1%
 
ValueCountFrequency (%) 
109.0725961< 0.1%
 
67.490851< 0.1%
 
48.7045241< 0.1%
 
44.245561< 0.1%
 
42.09851< 0.1%
 

OtherDebt
Real number (ℝ≥0)

Distinct4947
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.654460154
Minimum0
Maximum141.45915
Zeros1
Zeros (%)< 0.1%
Memory size39.1 KiB
2021-12-17T07:02:58.394222image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2876923
Q10.9803015
median2.09854
Q34.31478
95-th percentile11.8159808
Maximum141.45915
Range141.45915
Interquartile range (IQR)3.3344785

Descriptive statistics

Standard deviation5.395171563
Coefficient of variation (CV)1.476325185
Kurtosis125.1452338
Mean3.654460154
Median Absolute Deviation (MAD)1.3518535
Skewness7.589924316
Sum18272.30077
Variance29.10787619
MonotocityNot monotonic
2021-12-17T07:02:58.589114image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.11283230.1%
 
0.97297230.1%
 
0.5250962< 0.1%
 
0.90242< 0.1%
 
3.838242< 0.1%
 
1.845482< 0.1%
 
1.1316242< 0.1%
 
1.523882< 0.1%
 
0.758882< 0.1%
 
2.1150722< 0.1%
 
Other values (4937)497899.6%
 
ValueCountFrequency (%) 
01< 0.1%
 
0.0167041< 0.1%
 
0.0206361< 0.1%
 
0.021211< 0.1%
 
0.0224061< 0.1%
 
ValueCountFrequency (%) 
141.459151< 0.1%
 
102.3084041< 0.1%
 
66.92791< 0.1%
 
59.9101921< 0.1%
 
59.376241< 0.1%
 

LoanDefault
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2
3829 
1
1171 
ValueCountFrequency (%) 
2382976.6%
 
1117123.4%
 
2021-12-17T07:02:58.775583image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:02:58.872356image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:58.975221image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

MaritalStatus
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2
2599 
1
2401 
ValueCountFrequency (%) 
2259952.0%
 
1240148.0%
 
2021-12-17T07:02:59.131793image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:02:59.232560image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:59.313359image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

HouseholdSize
Real number (ℝ≥0)

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2004
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:02:59.414940image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.391627524
Coefficient of variation (CV)0.6324429758
Kurtosis1.021904688
Mean2.2004
Median Absolute Deviation (MAD)1
Skewness1.231984407
Sum11002
Variance1.936627165
MonotocityNot monotonic
2021-12-17T07:02:59.524884image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
1204040.8%
 
2146629.3%
 
355211.0%
 
452010.4%
 
52875.7%
 
6971.9%
 
7290.6%
 
870.1%
 
92< 0.1%
 
ValueCountFrequency (%) 
1204040.8%
 
2146629.3%
 
355211.0%
 
452010.4%
 
52875.7%
 
ValueCountFrequency (%) 
92< 0.1%
 
870.1%
 
7290.6%
 
6971.9%
 
52875.7%
 

NumberPets
Real number (ℝ≥0)

ZEROS

Distinct20
Distinct (%)0.4%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.066680016
Minimum0
Maximum21
Zeros1529
Zeros (%)30.6%
Memory size39.1 KiB
2021-12-17T07:02:59.656392image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile10
Maximum21
Range21
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.415624716
Coefficient of variation (CV)1.11378582
Kurtosis0.8960430159
Mean3.066680016
Median Absolute Deviation (MAD)2
Skewness1.194284162
Sum15315
Variance11.6664922
MonotocityNot monotonic
2021-12-17T07:02:59.766378image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
0152930.6%
 
177915.6%
 
258411.7%
 
33767.5%
 
52986.0%
 
42835.7%
 
62555.1%
 
72454.9%
 
81783.6%
 
91703.4%
 
Other values (10)2975.9%
 
ValueCountFrequency (%) 
0152930.6%
 
177915.6%
 
258411.7%
 
33767.5%
 
42835.7%
 
ValueCountFrequency (%) 
211< 0.1%
 
1930.1%
 
181< 0.1%
 
1690.2%
 
15100.2%
 

NumberCats
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)0.1%
Missing7
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.5003004206
Minimum0
Maximum6
Zeros3408
Zeros (%)68.2%
Memory size39.1 KiB
2021-12-17T07:02:59.898841image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8604850988
Coefficient of variation (CV)1.719936789
Kurtosis3.510210803
Mean0.5003004206
Median Absolute Deviation (MAD)0
Skewness1.880620155
Sum2498
Variance0.7404346052
MonotocityNot monotonic
2021-12-17T07:02:59.998744image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
0340868.2%
 
192218.4%
 
24639.3%
 
31593.2%
 
4340.7%
 
550.1%
 
62< 0.1%
 
(Missing)70.1%
 
ValueCountFrequency (%) 
0340868.2%
 
192218.4%
 
24639.3%
 
31593.2%
 
4340.7%
 
ValueCountFrequency (%) 
62< 0.1%
 
550.1%
 
4340.7%
 
31593.2%
 
24639.3%
 

NumberDogs
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)0.1%
Missing8
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.3928285256
Minimum0
Maximum7
Zeros3755
Zeros (%)75.1%
Memory size39.1 KiB
2021-12-17T07:03:00.128716image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.796539206
Coefficient of variation (CV)2.027702048
Kurtosis5.867107893
Mean0.3928285256
Median Absolute Deviation (MAD)0
Skewness2.328315171
Sum1961
Variance0.6344747067
MonotocityNot monotonic
2021-12-17T07:03:00.238617image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
0375575.1%
 
171914.4%
 
23607.2%
 
31172.3%
 
4360.7%
 
540.1%
 
71< 0.1%
 
(Missing)80.2%
 
ValueCountFrequency (%) 
0375575.1%
 
171914.4%
 
23607.2%
 
31172.3%
 
4360.7%
 
ValueCountFrequency (%) 
71< 0.1%
 
540.1%
 
4360.7%
 
31172.3%
 
23607.2%
 

NumberBirds
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)0.1%
Missing34
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean0.1111558598
Minimum0
Maximum5
Zeros4664
Zeros (%)93.3%
Memory size39.1 KiB
2021-12-17T07:03:00.359751image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4958319659
Coefficient of variation (CV)4.460691201
Kurtosis29.58998563
Mean0.1111558598
Median Absolute Deviation (MAD)0
Skewness5.226759949
Sum552
Variance0.2458493384
MonotocityNot monotonic
2021-12-17T07:03:00.460857image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
0466493.3%
 
11442.9%
 
2881.8%
 
3491.0%
 
4200.4%
 
51< 0.1%
 
(Missing)340.7%
 
ValueCountFrequency (%) 
0466493.3%
 
11442.9%
 
2881.8%
 
3491.0%
 
4200.4%
 
ValueCountFrequency (%) 
51< 0.1%
 
4200.4%
 
3491.0%
 
2881.8%
 
11442.9%
 

HomeOwner
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing13
Missing (%)0.3%
Memory size39.1 KiB
1
3140 
0
1847 
(Missing)
 
13
ValueCountFrequency (%) 
1314062.8%
 
0184736.9%
 
(Missing)130.3%
 
2021-12-17T07:03:00.540820image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

CarsOwned
Real number (ℝ≥0)

ZEROS

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1306
Minimum0
Maximum8
Zeros497
Zeros (%)9.9%
Memory size39.1 KiB
2021-12-17T07:03:00.612350image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.307472958
Coefficient of variation (CV)0.6136642065
Kurtosis0.3283876837
Mean2.1306
Median Absolute Deviation (MAD)1
Skewness0.5017223598
Sum10653
Variance1.709485537
MonotocityNot monotonic
2021-12-17T07:03:00.722331image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
2160732.1%
 
1111922.4%
 
3108221.6%
 
04979.9%
 
44819.6%
 
51493.0%
 
6511.0%
 
7130.3%
 
81< 0.1%
 
ValueCountFrequency (%) 
04979.9%
 
1111922.4%
 
2160732.1%
 
3108221.6%
 
44819.6%
 
ValueCountFrequency (%) 
81< 0.1%
 
7130.3%
 
6511.0%
 
51493.0%
 
44819.6%
 

CarOwnership
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Own
3704 
Lease
799 
-1
497 
ValueCountFrequency (%) 
Own370474.1%
 
Lease79916.0%
 
-14979.9%
 
2021-12-17T07:03:00.853723image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:00.945404image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:01.035588image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length3
Mean length3.2202
Min length2

CarBrand
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Domestic
2287 
Foreign
2216 
-1
497 
ValueCountFrequency (%) 
Domestic228745.7%
 
Foreign221644.3%
 
-14979.9%
 
2021-12-17T07:03:01.175473image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:01.275453image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:01.385364image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length7
Mean length6.9604
Min length2

CarValue
Categorical

HIGH CARDINALITY

Distinct801
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$(1,000.00)
497 
$9,800.00
 
25
$6,300.00
 
24
$13,500.00
 
24
$13,000.00
 
23
Other values (796)
4407 
ValueCountFrequency (%) 
$(1,000.00)4979.9%
 
$9,800.00 250.5%
 
$6,300.00 240.5%
 
$13,500.00 240.5%
 
$13,000.00 230.5%
 
$10,200.00 230.5%
 
$9,900.00 220.4%
 
$11,400.00 220.4%
 
$10,000.00 220.4%
 
$9,200.00 220.4%
 
Other values (791)429685.9%
 
2021-12-17T07:03:01.579405image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique204 ?
Unique (%)4.1%
2021-12-17T07:03:02.451353image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length12
Mean length11.8204
Min length11

CommuteTime
Categorical

Distinct42
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
24
336 
23
335 
27
 
331
25
 
330
22
 
325
Other values (37)
3343 
ValueCountFrequency (%) 
243366.7%
 
233356.7%
 
273316.6%
 
253306.6%
 
223256.5%
 
263116.2%
 
213076.1%
 
282935.9%
 
292605.2%
 
302264.5%
 
Other values (32)194638.9%
 
2021-12-17T07:03:02.632846image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)0.1%
2021-12-17T07:03:02.782912image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length2
Mean length2.0002
Min length1
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3093 
Yes
1907 
ValueCountFrequency (%) 
No309361.9%
 
Yes190738.1%
 
2021-12-17T07:03:02.875607image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Votes
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Yes
2590 
No
2410 
ValueCountFrequency (%) 
Yes259051.8%
 
No241048.2%
 
2021-12-17T07:03:02.915621image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

CreditCard
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Disc
1344 
Visa
1247 
Mast
1200 
AMEX
986 
Othe
223 
ValueCountFrequency (%) 
Disc134426.9%
 
Visa124724.9%
 
Mast120024.0%
 
AMEX98619.7%
 
Othe2234.5%
 
2021-12-17T07:03:03.010783image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:03.104789image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:03.204778image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

CardTenure
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct41
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.6558
Minimum0
Maximum40
Zeros91
Zeros (%)1.8%
Memory size39.1 KiB
2021-12-17T07:03:03.341032image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median14
Q326
95-th percentile38
Maximum40
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation12.02095783
Coefficient of variation (CV)0.7217280362
Kurtosis-1.056112126
Mean16.6558
Median Absolute Deviation (MAD)9
Skewness0.4293605803
Sum83279
Variance144.503427
MonotocityNot monotonic
2021-12-17T07:03:03.500948image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
32464.9%
 
12284.6%
 
22204.4%
 
41933.9%
 
51883.8%
 
61763.5%
 
71633.3%
 
111583.2%
 
81583.2%
 
91533.1%
 
Other values (31)311762.3%
 
ValueCountFrequency (%) 
0911.8%
 
12284.6%
 
22204.4%
 
32464.9%
 
41933.9%
 
ValueCountFrequency (%) 
401262.5%
 
391132.3%
 
38982.0%
 
37831.7%
 
36721.4%
 

CardItemsMonthly
Real number (ℝ≥0)

Distinct24
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.1774
Minimum0
Maximum23
Zeros7
Zeros (%)0.1%
Memory size39.1 KiB
2021-12-17T07:03:03.642517image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median10
Q312
95-th percentile16
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.391139809
Coefficient of variation (CV)0.3332029604
Kurtosis0.1581612106
Mean10.1774
Median Absolute Deviation (MAD)2
Skewness0.1985940773
Sum50887
Variance11.49982921
MonotocityNot monotonic
2021-12-17T07:03:03.772445image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
1160112.0%
 
1059111.8%
 
958611.7%
 
84979.9%
 
124979.9%
 
74118.2%
 
133547.1%
 
62955.9%
 
142805.6%
 
151953.9%
 
Other values (14)69313.9%
 
ValueCountFrequency (%) 
070.1%
 
1200.4%
 
2240.5%
 
3390.8%
 
41002.0%
 
ValueCountFrequency (%) 
232< 0.1%
 
221< 0.1%
 
2180.2%
 
20160.3%
 
19280.6%
 

CardSpendMonth
Categorical

HIGH CARDINALITY
UNIFORM

Distinct4760
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$-
 
7
$1,869.10
 
4
$2,311.40
 
3
$3,211.90
 
3
$2,458.40
 
3
Other values (4755)
4980 
ValueCountFrequency (%) 
$- 70.1%
 
$1,869.10 40.1%
 
$2,311.40 30.1%
 
$3,211.90 30.1%
 
$2,458.40 30.1%
 
$2,371.60 30.1%
 
$4,129.90 30.1%
 
$2,023.10 30.1%
 
$2,490.00 30.1%
 
$1,225.40 30.1%
 
Other values (4750)496599.3%
 
2021-12-17T07:03:03.944123image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4535 ?
Unique (%)90.7%
2021-12-17T07:03:04.080315image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length11
Mean length10.8956
Min length6
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2670 
Yes
2330 
ValueCountFrequency (%) 
No267053.4%
 
Yes233046.6%
 
2021-12-17T07:03:04.160269image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

PhoneCoTenure
Real number (ℝ≥0)

HIGH CORRELATION

Distinct73
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.2048
Minimum0
Maximum72
Zeros3
Zeros (%)0.1%
Memory size39.1 KiB
2021-12-17T07:03:04.260218image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q118
median38
Q359
95-th percentile72
Maximum72
Range72
Interquartile range (IQR)41

Descriptive statistics

Standard deviation22.66188803
Coefficient of variation (CV)0.5931686079
Kurtosis-1.330461631
Mean38.2048
Median Absolute Deviation (MAD)21
Skewness-0.03634538348
Sum191024
Variance513.5611692
MonotocityNot monotonic
2021-12-17T07:03:04.430575image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
722515.0%
 
711472.9%
 
70982.0%
 
5941.9%
 
69941.9%
 
9881.8%
 
7871.7%
 
2811.6%
 
64791.6%
 
68791.6%
 
Other values (63)390278.0%
 
ValueCountFrequency (%) 
030.1%
 
1721.4%
 
2811.6%
 
3751.5%
 
4711.4%
 
ValueCountFrequency (%) 
722515.0%
 
711472.9%
 
70982.0%
 
69941.9%
 
68791.6%
 

VoiceLastMonth
Categorical

HIGH CARDINALITY

Distinct866
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$12.60
 
31
$15.00
 
29
$23.70
 
28
$16.95
 
25
$22.50
 
25
Other values (861)
4862 
ValueCountFrequency (%) 
$12.60 310.6%
 
$15.00 290.6%
 
$23.70 280.6%
 
$16.95 250.5%
 
$22.50 250.5%
 
$11.85 240.5%
 
$15.45 240.5%
 
$14.85 240.5%
 
$14.25 240.5%
 
$12.90 230.5%
 
Other values (856)474394.9%
 
2021-12-17T07:03:04.622028image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique291 ?
Unique (%)5.8%
2021-12-17T07:03:04.771949image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length8
Mean length7.9908
Min length7

VoiceOverTenure
Categorical

HIGH CARDINALITY
UNIFORM

Distinct4438
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$2.05
 
8
$2.60
 
6
$14.30
 
5
$16.45
 
5
$42.05
 
4
Other values (4433)
4972 
ValueCountFrequency (%) 
$2.05 80.2%
 
$2.60 60.1%
 
$14.30 50.1%
 
$16.45 50.1%
 
$42.05 40.1%
 
$1.40 40.1%
 
$6.20 40.1%
 
$1.85 40.1%
 
$70.40 40.1%
 
$289.75 40.1%
 
Other values (4428)495299.0%
 
2021-12-17T07:03:04.945068image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3969 ?
Unique (%)79.4%
2021-12-17T07:03:05.104945image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length9
Mean length9.1692
Min length7
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3296 
Yes
1704 
ValueCountFrequency (%) 
No329665.9%
 
Yes170434.1%
 
2021-12-17T07:03:05.184946image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

EquipmentLastMonth
Categorical

HIGH CARDINALITY

Distinct735
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$-
3296 
$31.35
 
8
$38.80
 
8
$36.50
 
8
$32.30
 
8
Other values (730)
1672 
ValueCountFrequency (%) 
$- 329665.9%
 
$31.35 80.2%
 
$38.80 80.2%
 
$36.50 80.2%
 
$32.30 80.2%
 
$31.15 80.2%
 
$32.65 70.1%
 
$26.60 70.1%
 
$31.50 70.1%
 
$43.25 70.1%
 
Other values (725)163632.7%
 
2021-12-17T07:03:05.304838image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique295 ?
Unique (%)5.9%
2021-12-17T07:03:05.484302image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length6
Mean length6.6818
Min length6

EquipmentOverTenure
Categorical

HIGH CARDINALITY

Distinct1683
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$-
3296 
$101.05
 
2
$30.60
 
2
$699.70
 
2
$1,918.80
 
2
Other values (1678)
1696 
ValueCountFrequency (%) 
$- 329665.9%
 
$101.05 2< 0.1%
 
$30.60 2< 0.1%
 
$699.70 2< 0.1%
 
$1,918.80 2< 0.1%
 
$40.50 2< 0.1%
 
$1,463.55 2< 0.1%
 
$2,765.15 2< 0.1%
 
$572.85 2< 0.1%
 
$153.50 2< 0.1%
 
Other values (1673)168633.7%
 
2021-12-17T07:03:05.655765image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1660 ?
Unique (%)33.2%
2021-12-17T07:03:05.804857image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length6
Mean length7.375
Min length6
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Yes
3581 
No
1419 
ValueCountFrequency (%) 
Yes358171.6%
 
No141928.4%
 
2021-12-17T07:03:05.877618image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3656 
Yes
1344 
ValueCountFrequency (%) 
No365673.1%
 
Yes134426.9%
 
2021-12-17T07:03:05.927603image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

DataLastMonth
Categorical

HIGH CARDINALITY

Distinct746
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$-
3656 
$34.30
 
9
$32.20
 
7
$22.95
 
7
$27.95
 
7
Other values (741)
1314 
ValueCountFrequency (%) 
$- 365673.1%
 
$34.30 90.2%
 
$32.20 70.1%
 
$22.95 70.1%
 
$27.95 70.1%
 
$22.50 60.1%
 
$39.30 60.1%
 
$40.70 50.1%
 
$27.75 50.1%
 
$38.90 50.1%
 
Other values (736)128725.7%
 
2021-12-17T07:03:06.047535image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique394 ?
Unique (%)7.9%
2021-12-17T07:03:06.207852image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length6
Mean length6.54
Min length6

DataOverTenure
Categorical

HIGH CARDINALITY

Distinct1328
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
$-
3656 
$958.45
 
2
$2,279.80
 
2
$14.90
 
2
$2,323.80
 
2
Other values (1323)
1336 
ValueCountFrequency (%) 
$- 365673.1%
 
$958.45 2< 0.1%
 
$2,279.80 2< 0.1%
 
$14.90 2< 0.1%
 
$2,323.80 2< 0.1%
 
$2,049.85 2< 0.1%
 
$23.15 2< 0.1%
 
$2,182.05 2< 0.1%
 
$1,229.50 2< 0.1%
 
$1,199.20 2< 0.1%
 
Other values (1318)132626.5%
 
2021-12-17T07:03:06.386621image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1310 ?
Unique (%)26.2%
2021-12-17T07:03:06.580352image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length6
Mean length7.0918
Min length6

Multiline
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2558 
Yes
2442 
ValueCountFrequency (%) 
No255851.2%
 
Yes244248.8%
 
2021-12-17T07:03:06.685087image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

VM
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3485 
Yes
1515 
ValueCountFrequency (%) 
No348569.7%
 
Yes151530.3%
 
2021-12-17T07:03:06.743039image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Pager
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3782 
Yes
1218 
ValueCountFrequency (%) 
No378275.6%
 
Yes121824.4%
 
2021-12-17T07:03:06.797894image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Internet
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2498 
Yes
774 
3
598 
4
585 
2
545 
ValueCountFrequency (%) 
No249850.0%
 
Yes77415.5%
 
359812.0%
 
458511.7%
 
254510.9%
 
2021-12-17T07:03:06.913583image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:07.034259image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:07.162916image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length1.8092
Min length1

CallerID
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2624 
Yes
2376 
ValueCountFrequency (%) 
No262452.5%
 
Yes237647.5%
 
2021-12-17T07:03:07.274879image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

CallWait
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2605 
Yes
2395 
ValueCountFrequency (%) 
No260552.1%
 
Yes239547.9%
 
2021-12-17T07:03:07.327737image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2597 
Yes
2403 
ValueCountFrequency (%) 
No259751.9%
 
Yes240348.1%
 
2021-12-17T07:03:07.383590image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2610 
Yes
2390 
ValueCountFrequency (%) 
No261052.2%
 
Yes239047.8%
 
2021-12-17T07:03:07.443393image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

EBilling
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
3257 
Yes
1743 
ValueCountFrequency (%) 
No325765.1%
 
Yes174334.9%
 
2021-12-17T07:03:07.502589image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

TVWatchingHours
Real number (ℝ≥0)

ZEROS

Distinct32
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.645
Minimum0
Maximum36
Zeros85
Zeros (%)1.7%
Memory size39.1 KiB
2021-12-17T07:03:07.625444image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q117
median20
Q323
95-th percentile28
Maximum36
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.165608551
Coefficient of variation (CV)0.2629477501
Kurtosis2.348421771
Mean19.645
Median Absolute Deviation (MAD)3
Skewness-0.6447121586
Sum98225
Variance26.6835117
MonotocityNot monotonic
2021-12-17T07:03:07.818977image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%) 
204519.0%
 
194458.9%
 
214408.8%
 
184138.3%
 
223717.4%
 
173507.0%
 
163096.2%
 
233016.0%
 
152635.3%
 
242485.0%
 
Other values (22)140928.2%
 
ValueCountFrequency (%) 
0851.7%
 
61< 0.1%
 
730.1%
 
890.2%
 
9130.3%
 
ValueCountFrequency (%) 
3630.1%
 
3560.1%
 
3490.2%
 
3380.2%
 
32100.2%
 

OwnsPC
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
Yes
3164 
No
1836 
ValueCountFrequency (%) 
Yes316463.3%
 
No183636.7%
 
2021-12-17T07:03:07.960079image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2604 
Yes
2396 
ValueCountFrequency (%) 
No260452.1%
 
Yes239647.9%
 
2021-12-17T07:03:08.017924image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2626 
Yes
2374 
ValueCountFrequency (%) 
No262652.5%
 
Yes237447.5%
 
2021-12-17T07:03:08.084529image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

OwnsFax
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
4106 
Yes
894 
ValueCountFrequency (%) 
No410682.1%
 
Yes89417.9%
 
2021-12-17T07:03:08.142266image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
No
2637 
Yes
2363 
ValueCountFrequency (%) 
No263752.7%
 
Yes236347.3%
 
2021-12-17T07:03:08.199116image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Gender_num
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing33
Missing (%)0.7%
Memory size39.1 KiB
2
2494 
1
2473 
ValueCountFrequency (%) 
2249449.9%
 
1247349.5%
 
(Missing)330.7%
 
2021-12-17T07:03:08.300204image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:08.402140image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:08.510808image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

LoanDefault_num
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
2
3829 
1
1171 
ValueCountFrequency (%) 
2382976.6%
 
1117123.4%
 
2021-12-17T07:03:08.654782image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:08.758095image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:08.858326image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2
1662 
1
1215 
3
1176 
4
947 
ValueCountFrequency (%) 
2166233.2%
 
1121524.3%
 
3117623.5%
 
494718.9%
 
2021-12-17T07:03:09.023533image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:09.143210image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:09.258528image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Age_Recoded
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
>31-47
1322 
18-31
1253 
>62
1238 
>47-62
1187 
ValueCountFrequency (%) 
>31-47132226.4%
 
18-31125325.1%
 
>62123824.8%
 
>47-62118723.7%
 
2021-12-17T07:03:09.419591image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:09.543532image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:09.674412image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length5.0066
Min length3
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
0-18
1304 
>59
1244 
>38-59
1239 
>18-38
1213 
ValueCountFrequency (%) 
0-18130426.1%
 
>59124424.9%
 
>38-59123924.8%
 
>18-38121324.3%
 
2021-12-17T07:03:09.852199image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:09.974906image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:10.110795image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.732
Min length3
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.1 KiB
1
2604 
2
2396 
ValueCountFrequency (%) 
1260452.1%
 
2239647.9%
 
2021-12-17T07:03:10.274365image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:10.380973image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:10.483682image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

HomeOwner2
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing13
Missing (%)0.3%
Memory size39.1 KiB
2
3140 
1
1847 
ValueCountFrequency (%) 
2314062.8%
 
1184736.9%
 
(Missing)130.3%
 
2021-12-17T07:03:10.645986image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-12-17T07:03:10.760240image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:03:10.863581image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

VoiceLastMonth_Coded
Real number (ℝ≥0)

Distinct866
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.41435
Minimum2.7
Maximum539.55
Zeros0
Zeros (%)0.0%
Memory size39.1 KiB
2021-12-17T07:03:11.045755image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum2.7
5-th percentile8.7
Q117.1
median28.65
Q349.65
95-th percentile110.2725
Maximum539.55
Range536.85
Interquartile range (IQR)32.55

Descriptive statistics

Standard deviation38.32014348
Coefficient of variation (CV)0.9481816107
Kurtosis18.50338971
Mean40.41435
Median Absolute Deviation (MAD)13.875
Skewness3.271922723
Sum202071.75
Variance1468.433396
MonotocityNot monotonic
2021-12-17T07:03:11.266554image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
12.6310.6%
 
15290.6%
 
23.7280.6%
 
22.5250.5%
 
16.95250.5%
 
14.25240.5%
 
11.85240.5%
 
14.85240.5%
 
15.45240.5%
 
13.8230.5%
 
Other values (856)474394.9%
 
ValueCountFrequency (%) 
2.72< 0.1%
 
2.851< 0.1%
 
31< 0.1%
 
3.151< 0.1%
 
3.32< 0.1%
 
ValueCountFrequency (%) 
539.551< 0.1%
 
420.61< 0.1%
 
3901< 0.1%
 
343.651< 0.1%
 
341.251< 0.1%
 

Interactions

2021-12-17T07:01:49.692499image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:49.858531image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.010646image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.210544image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.363123image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.507993image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.653809image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.803879image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:50.967200image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.127444image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.300122image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.457387image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.628852image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.768777image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:51.912291image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.062212image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.212558image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.368027image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.517911image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.669726image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.822572image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:52.987365image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.127302image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.287351image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.432867image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.591400image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.752812image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:53.909334image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:54.060044image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:54.216591image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:54.396827image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:54.569266image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:54.721553image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.034209image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.174426image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.317340image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.457265image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.607186image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.768524image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:55.921239image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.061162image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.197283image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.337239image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.477172image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.618564image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.739124image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:56.881751image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:57.021674image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:57.141610image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:01:57.276527image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
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2021-12-17T07:02:28.096777image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:28.273909image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:28.555124image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:28.759578image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:29.029855image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:29.288165image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:29.537989image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:29.734008image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:29.911122image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.080997image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.229342image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.386933image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.536324image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.691602image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:30.848841image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.014294image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.169937image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.317149image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.464672image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.670040image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:31.848391image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.011393image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.207297image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.368045image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.525391image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.693825image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:32.851661image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:33.040241image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:33.232728image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:33.560228image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:33.832520image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.125137image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.328032image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.513824image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.660898image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.842300image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:34.998114image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.148868image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.323704image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.470142image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.600078image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.784019image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:35.939194image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.072393image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.211745image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.349818image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.479473image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.628101image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.790505image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:36.952107image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.132233image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.284817image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.434740image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.595481image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.742046image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:37.875288image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.052418image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.205003image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.357399image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.485954image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.617346image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.763915image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:38.893818image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:39.033748image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:39.183667image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:39.320105image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:39.453727image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:39.607399image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:40.116906image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:40.256842image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:40.395647image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
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2021-12-17T07:02:40.663247image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
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2021-12-17T07:02:41.074854image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:41.224815image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:41.364734image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
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2021-12-17T07:02:42.137905image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:42.304835image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:42.454683image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:42.635195image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:42.816789image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.003173image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.210758image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.398259image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.565709image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.704690image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.850843image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:43.982599image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.130615image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.267488image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.407415image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.553194image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.713687image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:44.877114image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.028710image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.206033image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.389542image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.548201image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.714926image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:45.883996image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Correlations

2021-12-17T07:03:11.476793image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-12-17T07:03:11.865717image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-12-17T07:03:12.244290image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-12-17T07:03:12.656809image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-12-17T07:03:13.957500image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-12-17T07:02:46.468532image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:51.040444image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:52.561824image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2021-12-17T07:02:52.931076image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Sample

First rows

CustomerIDRegionTownSizeGenderAgeEducationYearsJobCategoryUnionMemberEmploymentLengthRetiredHHIncomeDebtToIncomeRatioCreditDebtOtherDebtLoanDefaultMaritalStatusHouseholdSizeNumberPetsNumberCatsNumberDogsNumberBirdsHomeOwnerCarsOwnedCarOwnershipCarBrandCarValueCommuteTimePoliticalPartyMemVotesCreditCardCardTenureCardItemsMonthlyCardSpendMonthActiveLifestylePhoneCoTenureVoiceLastMonthVoiceOverTenureEquipmentRentalEquipmentLastMonthEquipmentOverTenureCallingCardWirelessDataDataLastMonthDataOverTenureMultilineVMPagerInternetCallerIDCallWaitCallForwardThreeWayCallingEBillingTVWatchingHoursOwnsPCOwnsMobileDeviceOwnsGameSystemOwnsFaxNewsSubscriberGender_numLoanDefault_numDebtToIncomeRatio_RecodedAge_RecodedPhoneCoTenure_CodedOwnsMobileDevice_CodedHomeOwner2VoiceLastMonth_Coded
03964-QJWTRG-NPN12Female2015ProfessionalYes0No31000.011.11.2009092.240091123.00.00.00.00.00.02OwnDomestic$14,300.0022YesYesMast25$816.60No5$19.50$34.40Yes$29.50$126.10YesNo$-$-YesYesYesNoNoYesYesYesNo13NoYesYesNoNo2.01318-310-1821.019.50
10648-AIPJSP-UVM55Male2217SalesNo0No15000.018.61.2220201.567980122.06.00.00.00.01.02OwnForeign$6,800.0029YesNoVisa45$426.00Yes39$26.70$330.60Yes$54.85$1,975.00YesYes$45.65$1,683.55YesYesYes4YesNoYesNoYes18YesYesYesYesYes1.01418-31>38-5922.026.70
25195-TLUDJE-HVO34Female6714SalesNo16No35000.09.90.9286202.536380213.03.02.01.00.01.03OwnForeign$18,800.0024YesNoVisa359$1,842.20No65$85.20$1,858.35No$-$-YesNo$-$-YesNoNoNoNoNoNoNoNo21NoNoNoNoYes2.022>62>5912.085.20
34459-VLPQUH-3OL43Male2316SalesNo0No20000.05.70.0228001.117200115.00.00.00.00.01.03OwnForeign$8,700.0038NoNoVisa517$3,409.90Yes36$18.00$199.45No$-$-YesNo$-$-YesNoNo2NoNoNoNoYes26YesYesYesNoYes1.01218-31>18-3822.018.00
48158-SMTQFB-CNO22Male2616SalesNo1No23000.01.70.2146590.176341214.00.00.00.00.00.01LeaseForeign$10,600.0032NoNoDisc88$2,551.00Yes21$9.15$74.10No$-$-YesYes$19.05$410.80NoYesNo3YesYesYesYesNo27YesNoYesNoNo1.02118-31>18-3811.09.15
59662-FUSYIM-1IV44Male6417ServiceNo22No107000.05.61.0605844.931416221.011.01.01.00.01.00-1-1$(1,000.00)23NoNoVisa1811$2,282.70No28$24.30$264.90Yes$35.50$970.95YesNo$-$-NoNoYesNoYesYesYesYesNo21NoNoNoNoNo1.022>62>18-3812.024.30
67432-QKQFJJ-K7225Female5214ProfessionalNo10No77000.01.90.5018090.961191221.02.00.02.00.00.02OwnDomestic$25,600.0032NoNoOthe320$8,223.20No15$11.40$44.80No$-$-NoNo$-$-NoNoNoYesNoNoYesNoNo19YesYesNoNoNo2.021>47-620-1821.011.40
78959-RZWRHU-ST834Female4416ProfessionalNo11No97000.014.45.9503688.017632212.010.00.02.00.01.01OwnDomestic$55,500.0031NoYesAMEX256$5,927.00No46$44.55$612.70No$-$-YesNo$-$-YesNoNoNoYesYesYesYesNo13NoNoNoNoYes2.023>31-47>38-5912.044.55
89124-DZALHM-S6I23Female6612ProfessionalNo15Yes16000.02.60.1023360.313664221.01.01.00.00.01.01OwnForeign$8,600.0025YesYesMast2612$3,265.90Yes53$63.15$1,074.35No$-$-YesNo$-$-YesNoNoNoNoNoNoNoNo25NoNoNoNoNo2.021>62>38-5912.063.15
93512-MUWBGY-52X22Male4711LaborNo19No84000.04.11.7702161.673784222.01.01.00.00.01.04OwnDomestic$41,000.0029YesYesOthe211$1,996.40Yes3$10.95$20.05No$-$-NoNo$-$-NoNoNoNoNoNoNoNoNo21NoNoNoNoNo1.021>31-470-1812.010.95

Last rows

CustomerIDRegionTownSizeGenderAgeEducationYearsJobCategoryUnionMemberEmploymentLengthRetiredHHIncomeDebtToIncomeRatioCreditDebtOtherDebtLoanDefaultMaritalStatusHouseholdSizeNumberPetsNumberCatsNumberDogsNumberBirdsHomeOwnerCarsOwnedCarOwnershipCarBrandCarValueCommuteTimePoliticalPartyMemVotesCreditCardCardTenureCardItemsMonthlyCardSpendMonthActiveLifestylePhoneCoTenureVoiceLastMonthVoiceOverTenureEquipmentRentalEquipmentLastMonthEquipmentOverTenureCallingCardWirelessDataDataLastMonthDataOverTenureMultilineVMPagerInternetCallerIDCallWaitCallForwardThreeWayCallingEBillingTVWatchingHoursOwnsPCOwnsMobileDeviceOwnsGameSystemOwnsFaxNewsSubscriberGender_numLoanDefault_numDebtToIncomeRatio_RecodedAge_RecodedPhoneCoTenure_CodedOwnsMobileDevice_CodedHomeOwner2VoiceLastMonth_Coded
49903192-STGTEL-D1433Female2621CraftsYes0No89000.09.32.0858046.191196121.07.00.02.00.01.05OwnForeign$47,100.0031NoNoAMEX311$4,407.50No11$13.95$40.60Yes$39.15$374.80YesYes$35.70$355.75YesYesYesYesYesYesYesYesYes22YesYesYesYesNo2.01218-310-1822.013.95
49916841-FBQILD-2CH22Female5918SalesNo9No75000.014.23.6103507.039650212.01.00.01.00.01.01OwnDomestic$32,000.0019NoYesMast1210$2,856.70No35$19.35$197.60Yes$41.20$1,402.20NoYes$34.40$1,140.55YesYesYes3YesNoYesNoYes25YesYesYesYesNo2.023>47-62>18-3822.019.35
49926309-HRNBPZ-56544Female5515SalesNo10No49000.00.50.1149050.130095221.00.00.00.00.01.00-1-1$(1,000.00)37NoNoAMEX209$8,888.30No52$21.60$373.05No$-$-YesNo$-$-NoYesYesNoYesYesYesYesNo15YesNoYesYesNo2.021>47-62>38-5912.021.60
49938563-YGTRBK-25I33Male5618SalesNo2No60000.02.10.2205001.039500212.02.02.00.00.01.03OwnDomestic$31,900.0025NoYesDisc197$2,272.50Yes48$42.60$736.55No$-$-NoNo$-$-NoNoNoNoYesYesNoYesNo19YesNoYesYesNo1.021>47-62>38-5912.042.60
49941973-VJDGJA-TQ631Female3515SalesNo1No53000.011.33.2520272.736973122.01.00.01.00.00.01OwnForeign$31,900.0024NoYesMast316$4,308.00Yes7$5.55$11.75No$-$-NoNo$-$-NoNoNoNoYesNoYesNoNo23NoNoYesNoNo2.013>31-470-1811.05.55
49953675-GZFGOT-QJN22Male6810ProfessionalNo24No196000.08.07.9340807.745920221.04.04.00.00.01.01OwnDomestic$64,500.0021NoYesAMEX3511$8,721.10No69$102.30$2,405.90No$-$-YesNo$-$-NoNoNoNoNoNoNoNoNo19NoNoNoNoYes1.022>62>5912.0102.30
49964699-LEPCCE-3UD33Male5114ProfessionalNo6No83000.015.03.3366009.113400121.01.00.00.00.01.02OwnForeign$40,000.0026NoNoMast156$2,108.10Yes30$31.20$289.00No$-$-YesYes$27.90$757.35NoNoNoNoYesYesYesYesNo14NoNoNoNoNo1.013>47-62>18-3812.031.20
49978485-LLUICH-CVV45Male7517ProfessionalNo24No108000.010.83.5575208.106480221.00.00.00.00.01.03OwnDomestic$53,600.0032NoNoAMEX4011$8,840.80No72$88.20$2,109.25No$-$-YesNo$-$-YesNoNoNoYesYesYesYesNo16NoNoNoNoYes1.023>62>5912.088.20
49989325-URAAUT-7FA11Male4719SalesNo3No189000.010.85.02135215.390648114.00.00.00.00.01.02OwnForeign$96,000.0012YesNoMast229$3,813.50No37$23.85$282.70Yes$29.55$1,032.85YesNo$-$-YesNoNo3NoNoNoNoYes24YesYesYesNoYes1.013>31-47>18-3822.023.85
49998027-EXDZBF-OGR35Female4110CraftsNo20No77000.06.22.2676502.506350212.09.00.00.00.01.02OwnDomestic$49,300.0032YesYesMast167$2,697.20Yes25$24.15$197.25No$-$-YesNo$-$-NoNoNoNoNoNoNoNoNo19NoNoNoNoNo2.022>31-47>18-3812.024.15